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Lead DevRel by testing how developers now discover, build, and get help—not by assuming the old playbook still covers every workflow. Keep documentation accurate and easy to retrieve, demonstrate practical AI use, carry developer feedback into product decisions, and measure outcomes that match your team’s mandate. “Stop playing it safe” is a call to learn deliberately in public, not a claim that every team should become an AI team or abandon its existing channels.
What changes when developers work with AI?
The familiar DevRel formula—good onboarding, useful documentation, technical content, and a presence at events—still matters. But developers may now do more work inside an IDE or with an AI assistant, and they may encounter product answers through AI tools rather than by navigating directly to a documentation site. That can change where friction appears and which examples developers encounter.
DevRel.ai’s practitioner essay, “The Old DevRel Playbook”, poses a useful question: “What tasks do developers currently accomplish by visiting your console that they could solve in the IDE via an agent?” Treat this as a prompt for investigation, not proof that a particular workflow has already moved. Map how your own developers discover, try, deploy, and troubleshoot the product, then validate assumptions with conversations and product-use evidence.
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How should a DevRel leader respond?
1. Map changing workflows before changing the whole program
Follow the path from first discovery through initial success, production use, and ongoing support. At each stage, ask where developers go for answers: an IDE, a coding assistant, an agent, a console, documentation, community channels, or a person on your team. Identify repeated friction and test which parts of the journey are actually changing.
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Use that map to decide what to experiment with. The evidence does not establish that every DevRel team should replace events, abandon SEO, or reorganize around AI. Keep channels that serve developers; adapt them when observed behavior gives you a reason.
2. Demonstrate useful work, including the limits
In her July 2025 DevRelCon New York talk, “DevRel’s biggest stage yet,” Block Global VP of Developer Relations Angie Jones described her team pivoting to an AI product after its earlier product was sunset. Her advice emphasizes transparent learning, practical use cases, adapting to AI-mediated discovery, and teaching beyond a technical audience when that serves the organization. She said: “That ability though, to pivot without losing momentum, that is something that developer advocates already excel at.”
Rank #2
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- What You Get: Anker USB-C Hub (5-in-1, 4K HDMI), welcome guide, 18-month warranty, and our friendly customer service.
Make demonstrations reproducible and task-focused: show the developer’s goal, the steps that work, and where the AI tool or product falls short. Explain what the team knows and what remains uncertain. This is more useful than a polished spectacle that hides the conditions needed to reproduce its result.
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Outdated examples can be especially damaging when developers or AI assistants reuse them. Keep code samples, compatibility notes, migrations, and version labels aligned with the product as shipped. Structure documentation so that authoritative instructions are easy to locate and distinguish from obsolete guidance.
Rank #3
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A DevRelCon New York 2025 panel on AI developer relations recommended structured, version-labeled documentation, attention to actual model and integration use, and educational material useful to both people and AI assistants. These are practitioner recommendations, not a guaranteed format for retrieval. DevRel.ai also flags stale training knowledge and average or outdated examples as concerns. Track where developers and assistants are getting answers, then correct the underlying product guidance when it is wrong.
4. Keep the feedback loop connected to product decisions
DevRel helps developers succeed outwardly and brings their needs inward. Capture recurring friction with enough context for product and engineering teams to act: what the developer was trying to do, where the process failed, how often the issue appears, and what workaround people use. Report what changed in response—or why it did not—so developers can see that feedback has a destination.
Rank #4
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If the role is reduced to lead generation or content output, the two-way relationship can weaken. The DevRel Directory’s overview of Developer Relations and the DevRel Handbook both frame the work in terms of developer relationships and organizational connection. Protect time and access for that work alongside visible deliverables.
5. Teach adjacent teams when there is a clear need
Jones’s account includes educating non-technical groups as her organization adopted AI. That can help when colleagues are adopting AI products, influencing developer experience, or need a practical understanding of how developers use the tools. It does not mean every DevRel team should own company-wide AI training. Define the audience and purpose before taking on a broader teaching remit.
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How can a DevRel team show its impact?
Start with the team’s actual mandate, then choose a small number of indicators that connect its work to developer outcomes. Possible measures include successful onboarding, product use where it can be measured, the quality and resolution of developer issues, recurring friction addressed by product, and meaningful community participation. These are options, not a universal scorecard.
Pair numbers with concise examples of developer problems that led to a product change or a demonstrable improvement. This gives leaders context that a single activity count cannot provide, while avoiding unsupported claims that DevRel alone caused a business outcome.
Use survey findings as dated context, not as targets for your team. DevRel.Agency’s September 10, 2024 announcement of the 11th Annual State of Developer Relations Report said 78% of surveyed professionals used AI in their toolkit, 66% cited awareness and adoption as their top DevRel goal, 44% cited active users as a primary success measure, and 61% said proving DevRel influence was difficult. The separate 2024 State of Developer Relations survey reports that 42% selected content generation as an AI use, 28.8% selected code suggestions and completions, 15.2% selected documentation generation, and 60.7% named proving impact with data and metrics as a top challenge. These are publishers’ reported 2024 survey results; they do not establish a 2026 adoption rate or prove that AI caused a change in DevRel strategy.
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There is no evidence-backed org chart that fits every company. DevRel may report through marketing, product, open source, or another function; each placement creates different incentives and access. The practical question is whether the team can do the work its mandate requires.
- Decision access: Can the team bring developer evidence to product and engineering decision-makers?
- Mandate and measures: Are goals clear and compatible with the reporting line?
- Community trust: Is there room for candid education and two-way relationships, rather than only promotional output?
- Sponsorship and capacity: Is a leader able to protect resources and connect the work to company priorities?
DevRel Directory’s roles and responsibilities guide and Bear Douglas’s DevRelCon New York 2024 talk, “Successful DevRel no matter your org chart,” describe varied structures and trade-offs, not a single proven winner. Agree on the audience, scope, decision access, feedback route, measures, and executive sponsor. Whatever the reporting line, keep the work grounded in developer needs and accurate product information.
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